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Interaction with the Physical World

Advances in low- and no-power sensing, communication and interaction technologies offer new possibilities for blending digital innovation with our physical environment. 

From gesture recognition that allows people to interact with objects in new ways, to low-power sensors that collect and transmit data about temperature, air quality, urban accessibility and more, our researchers are tapping into the potential of computation to transform how we experience the world around us.


Research Groups & Labs

Robot Learning lab cover photo of robotic warthog/all terrain vehicle driving in the snow

Robot Learning Lab

The Robot Learning Lab works on foundational research in machine learning, AI and robotics to develop intelligent robotic systems that can perceive, plan and act in complex environments and improve performance with experience.

A person holds up a miniature sensor

Sensor Systems Laboratory

The Sensor Systems Laboratory invents new sensor systems, devises new ways to power and communicate with them, and develops algorithms for using them, with applications in the domains of bioelectronics, robotics, and ubiquitous computing.


Faculty Members

Faculty

Faculty

Faculty


Centers & Initiatives

Society + Technology is a cross-campus, cross-disciplinary initiative and community at the University of Washington that is dedicated to research, teaching and learning focused on the social, societal and justice dimensions of technology.

The Transportation Data Equity Initiative (TDEI) aims to enhance the quality and accessibility of travel services by building open source data collection and vetting tools, transportation data digital infrastructure, and governance frameworks that enable public-private data sharing and interoperability. The TDEI is a project sponsored by The Complete Trip, an ITS4US Deployment Program.

Highlights


UW News

Researchers in the Allen School’s UbiComp Lab created the ProxiCycle sensor system to get a handle on which routes are best — and worst — for bikes, finding a significant correlation between the sensor data and other indicators of cycling risk.

Allen School News

The ACM Special Interest Group on Computer-Human Interaction recognized Fogarty’s leadership and contributions to human-computer interaction research including ubiquitous computing, interactive machine learning, accessibility and personal health informatics.

Allen School News

A team of Allen School researchers introduced computational illusion knitting — a design framework that helps automate the process, making illusion knitting more accessible and allowing for more complex and multi-view patterns like hidden Mona Lisas that were previously believed to be impossible.

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